CBF-Based Multi-UAV Search

Introduction

This repository implements a multi-UAV search problem using a Control Barrier Function (CBF)-based approach. CBFs are a powerful mathematical tool used to ensure safety in dynamical systems by encoding safety constraints directly into the control laws of robots. For more information on CBFs, you can refer to the foundational paper: Control Barrier Functions: Theory and Applications.

The algorithm is implemented in C++, and the results are stored in .json files, which can be visualized using a Python script.

We recommend using CLion for development, as it provides an intuitive interface for managing CMake projects and supports Python scripting for result visualization.

Installation

Solver Configuration Guide

Supported Solvers

This project supports two optimization solvers: Gurobi and HiGHS. Both solvers need to be installed separately by the user, and you can choose to enable or disable them based on your installation.

Enabling Solvers

Each solver has a corresponding ENABLE_* option in the CMake configuration. You can enable or disable them depending on the solver you have installed. For example:

• If Gurobi is installed, set ENABLE_GUROBI to ON to enable Gurobi.
• If HiGHS is installed, set ENABLE_HIGHS to ON to enable HiGHS.

Installing Gurobi

If you choose to use Gurobi as the solver, refer to the official Gurobi installation guide:
Gurobi Installation Guide

After installing Gurobi, ensure to specify the Gurobi installation path using the -DGUROBI_HOME option during the CMake configuration:

cmake -DGUROBI_HOME=/opt/gurobi1200/linux64 ..

It is recommended to use CLion for configuring and building the project, as it simplifies the setup process. If you need to set environment variables when using CMake in CLion, you can refer to the CLion Environment Variables Guide.

Installing HiGHS

If you choose to use HiGHS as the solver, refer to the official HiGHS installation guide:
HiGHS Installation Guide

Once HiGHS is installed, CMake will automatically find and link the HiGHS library.

CMake Configuration and Solver Integration

The integration of Gurobi and HiGHS with CMake is based on their official documentation. Below are the relevant guides for integrating them:

• HiGHS Integration Guide for CMake Projects
• Gurobi CMake Project Guide

These documents provide detailed integration methods and configuration options to help you correctly link and use both solvers in your project.

Common Issues

• How to ensure CMake finds the correct shared libraries (.so or .dylib)? Please verify that the shared libraries (either .so or .dylib files) found by CMake match the required version for your platform. File names and paths may differ across platforms, so be sure to confirm that the versions are correct based on your system and the installed solver version.

Python Environment Setup

1. Install Anaconda or Miniconda

Download Anaconda (recommended for data science) or Miniconda (minimal installer), then follow default installation steps.

2. Create Python 3.11 Environment

conda create -n cbf_env python=3.11
conda activate cbf_env

This creates an isolated environment with Python 3.11.

3. Install FFmpeg

conda install -c conda-forge ffmpeg  # Handles codec dependencies automatically

4. Install Project Dependencies

pip install -r requirements.txt  # Use --force-reinstall if conflicts occur

5. CLion Integration

• Open File > Settings > Build > Python Interpreter.
• Click ⚙️ → Add → Conda Environment → Specify path:
  • Unix: conda_install_path/envs/cbf_env/bin/python
  • Windows: ...\envs\cbf_env\python.exe.

This streamlined workflow ensures dependency isolation and cross-platform compatibility. For advanced troubleshooting, refer to the original Chinese version.